Progress in artificial intelligence

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Progress in artificial intelligence (AI) refers to the advances, milestones, and breakthroughs that have been achieved in the field of artificial intelligence over time. AI is a multidisciplinary branch of computer science that aims to create machines and systems capable of performing tasks that typically require human intelligence. AI applications have been used in a wide range of fields including medical diagnosis, finance, robotics, law, video games, agriculture, and scientific discovery. However, many AI applications are not perceived as AI: "A lot of cutting-edge AI has filtered into general applications, often without being called AI because once something becomes useful enough and common enough it's not labeled AI anymore."^[1][2] "Many thousands of AI applications are deeply embedded in the infrastructure of every industry."^[3] In the late 1990s and early 2000s, AI technology became widely used as elements of larger systems,^[3][4] but the field was rarely credited for these successes at the time.

Kaplan and Haenlein structure artificial intelligence along three evolutionary stages:

1. Artificial narrow intelligence – AI capable only of specific tasks;
2. Artificial general intelligence – AI with ability in several areas, and able to autonomously solve problems they were never even designed for;
3. Artificial superintelligence – AI capable of general tasks, including scientific creativity, social skills, and general wisdom.^[2]

To allow comparison with human performance, artificial intelligence can be evaluated on constrained and well-defined problems. Such tests have been termed subject-matter expert Turing tests. Also, smaller problems provide more achievable goals and there are an ever-increasing number of positive results.

Humans still substantially outperform both GPT-4 and models trained on the ConceptARC benchmark that scored 60% on most, and 77% on one category, while humans 91% on all and 97% on one category.^[5]